E-RAFT: Dense Optical Flow from Event Cameras-Reference-Cited by-同舟云学术

E-RAFT: Dense Optical Flow from Event Cameras

Published:2021-12 Issue: Volume: Page:
ISSN:
Container-title:2021 International Conference on 3D Vision (3DV)
language:
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Author:

Gehrig Mathias,Millhausler Mario,Gehrig Daniel,Scaramuzza Davide

Funder

National Science Foundation

European Research Council

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9665713/9665818/09665931.pdf?arnumber=9665931

Reference41 articles.

1. MaskFlownet: Asymmetric Feature Matching With Learnable Occlusion Mask

2. Unsupervised learning of dense optical flow and depth from sparse event data;ye;ArXiv e-prints,2019

3. Models matter, so does training: An empirical study of cnns for optical flow estimation;sun;IEEE Transactions on Pattern Analysis and Machine Intelligence,2019

4. PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume

5. Two-stream convolutional networks for action recognition in videos;simonyan;Conf Neural Inf Process Syst,2014

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